广义线性频域Chirplet变换及其应用
Generalized Linear Frequency-Domain Chirplet Transform and Its Application
DOI: 10.12677/PM.2024.142063, PDF,   
作者: 毛怡婷：成都理工大学数理学院，四川 成都
关键词: 时频分析；Chirplet变换；群延迟；Time-Frequency Analysis； Chirplet Transform； Group Delay
摘要: 时频分析可以获取地下储层的相关信息，在储层表征中发挥着重要作用。本文提出了广义线性频域Chirplet变换(General linear Frequency-domain chirplet transform, GLFCT)，首先旋转时频基来匹配实际群延迟(group delay, GD)曲线，然后根据每一个时频点的振幅，得到最佳chirp率，最终得到高分辨率的时频表征结果。合成信号的数值验证结果证明了GLFCT处理瞬态信号的有效性，模拟地震记录的测试很好地证实了在储层表征方面的可行性。
Abstract: Time-frequency analysis can obtain the relevant information of underground reservoir, which plays an important role in reservoir characterization. In this paper, the General linear Frequency-domain chirplet transform (GLFCT) is proposed. Firstly, the time-frequency basis is rotated to match the actual group delay (GD) curve. Then, according to the amplitude of each time-frequency point, the optimal chirp rate is obtained, and finally the high-resolution time-frequency characterization results are obtained. The numerical verification results of the synthesized signal demonstrate the effectiveness of GLFCT in processing transient signals, and the test of simulated seismic records well proves the feasibility in reservoir characterization.
文章引用：毛怡婷. 广义线性频域Chirplet变换及其应用[J]. 理论数学, 2024, 14(2): 642-648. https://doi.org/10.12677/PM.2024.142063

参考文献

[1] Gabor, D. (1946) Theory of communication. Part 1: The Analysis of Information. Journal of the Institution of Electrical Engineers - Part III: Radio and Communication Engineering, 93, 429-441. [Google Scholar] [CrossRef] 
[2] Mallat, S.G. (2009) A Theory for Multiresolution Signal Decompo-sition: The Wavelet Representation. In: Heil, C. and Walnut, D.F., Eds., Fundamental Papers in Wavelet Theory. [Google Scholar] [CrossRef] 
[3] Stockwell, R.G., Mansinha, L. and Lowe, R.P. (1996) Localiza-tion of the Complex Spectrum: The S Transform. IEEE Transactions on Signal Processing, 44, 998-1001. [Google Scholar] [CrossRef] 
[4] Partyka, G., Gridley, J. and Lopez, J. (1999) Interpretational Applications of Spectral Decomposition in Reservoir Characterization. The Leading Edge, 18, 353-360. [Google Scholar] [CrossRef] 
[5] 高静怀, 汪文秉, 朱光明, 彭玉华，王玉贵. 地震资料处理中小波函数的选取研究[J]. 地球物理学报, 1996, 39(3): 392-400.
[6] Wang, B. and Lu, W. (2017) An Efficient Ampli-tude-Preserving Generalized S Transform and Its Application in Seismic Data Attenuation Compensation. IEEE Transactions on Geoscience and Remote Sensing, 56, 859-866. [Google Scholar] [CrossRef] 
[7] 高静怀, 刘乃豪, 吕奇, 张茁生, 姜秀娣, 陈树民. 型油气储层同步挤压变换域分析方法[J]. 石油物探, 2018, 57(4): 512-521.
[8] 范明霏, 吴胜和, 曲晶晶, 张佳佳. 基于广义S变换模极大值的薄储层刻画新方法[J]. 石油地球物理勘探, 2017, 52(4): 805-814.
[9] 田仁飞, 杨春峰, 胡宇, 杨振峰, 李秋菊. 识别岩性油藏薄储集层的谱分解技术[J]. 天然气地球科学, 2015, 26(2): 360-366.
[10] Wigner, E. (1932) On the Quantum Correction for Thermodynamic Equilibrium. Physical Review, 40, 749-759. [Google Scholar] [CrossRef] 
[11] Ville, J. (1948) Theorie et applications de la notion de signal analytique. Cables et Transmissions, 2, 61-74.
[12] 徐天吉, 程冰洁, 牛双晨. 基于最大熵准则的Wigner-Ville分布与微型古河道刻画方法及应用[J]. 石油勘探与开发, 2021, 48(6): 1175-1186.
[13] 尹继尧, 钟磊, 张吉辉. 基于连续小波变换目标处理技术在储层预测中的应用[J]. 石油物探, 2016, 55(3): 433-440.
[14] 纪永祯, 张渝悦, 朱立华. 基于SBL-WVD的地震高分辨率时频分析[J]. 石油物探, 2020, 59(1): 80-86.
[15] Mann, S. and Haykin, S. (1995) The Chirplet Transform: Physical Considerations. IEEE Transactions on Signal Processing, 43, 2745-2761. [Google Scholar] [CrossRef] 
[16] Yu, G. and Zhou, Y. (2016) General Linear Chirplet Transform. Mechan-ical Systems and Signal Processing, 70-71, 958-973. [Google Scholar] [CrossRef] 
[17] He, D., Cao, H., Wang, S. and Chen, X. (2019) Time-Reassigned Synchrosqueezing Transform: The Algorithm and Its Appli-cations in Mechanical Signal Processing. Mechanical Systems and Signal Processing, 117, 255-279. [Google Scholar] [CrossRef] 

为你推荐